European Data Collaboration Survey

KULTURDATA conducted a mini survey sponsored by DEN (www.den.nl) in early 2026 to test organizations willingness to share audience insights.

Why share data?

In an era of increasing complexity in audience behaviour, shifting cultural participation patterns, and growing pressure on public funding, cultural organisations face a shared challenge: the need to make better, more informed decisions about how they engage with their communities. Yet many organisations operate with limited visibility beyond their own walls — relying on siloed datasets that, in isolation, offer only a partial picture of the audiences they serve.

Data collaboration — the structured, consensual sharing of aggregated audience data across cultural organisations — presents a compelling opportunity to change this. When organisations pool anonymised, aggregated insights, they move beyond the constraints of individual data collection and begin to generate something far more powerful: a collective intelligence about cultural participation that no single organisation could produce alone.

This is not simply a technical or operational proposition. It is a strategic one. At its core, data collaboration is about building a shared evidence base that enables cultural leaders, funders, and policymakers to understand not just who is attending individual venues or events, but how, why, and under what conditions communities engage with culture more broadly. It shifts the conversation from reactive reporting to proactive, evidence-led strategy.

Why Aggregated Audience Data Matters

The cultural sector has long recognised the value of audience insight, but the depth and reach of that insight has traditionally been constrained by organisational boundaries, resource limitations, and the absence of interoperable data infrastructure. Individual audience surveys, box office records, and engagement metrics provide valuable snapshots — but they cannot, on their own, answer the broader questions that cultural strategy demands:

• Which communities are consistently underrepresented across the sector, not just within one organisation?

• How do participation patterns differ across geography, demography, and cultural form?

• Where are the gaps between cultural provision and community need?

• What does genuine cross-sector audience behaviour look like over time?

• Aggregated data — drawn from multiple organisations and analysed at a collective level — begins to answer these questions. It transforms fragmented organisational records into sector-level intelligence, providing the breadth and statistical robustness needed to identify meaningful trends, test assumptions, and drive impactful decision-making.

  
  

The Role of the Data Collaboration Canvas

The Data Collaboration Canvas provides a practical framework within which these ambitions can be responsibly realised. It offers cultural organisations a structured approach to navigating the considerations, agreements, and conditions necessary for meaningful data sharing — addressing questions of governance, trust, data standards, and mutual benefit. Rather than leaving organisations to navigate collaboration on an ad hoc basis, the Canvas creates a shared language and a common foundation upon which productive data partnerships can be built.

The survey findings presented in this report contribute directly to this framework. By capturing the perspectives, concerns, and motivations of cultural leaders regarding data sharing, this research helps identify the conditions under which collaboration is most likely to succeed — and the barriers that must be addressed to make it both equitable and sustainable.

The Data Collaboration Canvas for Arts & Culture

Key Survey Findings

A Sector Ready to Collaborate

Perhaps the most striking finding of this survey is the sheer strength of enthusiasm for data sharing among cultural sector professionals. When asked how likely they would be to recommend greater data sharing in the cultural sector, respondents gave an average rating of 9.41 out of 10 — an exceptional score that, in any measurement framework, signals not merely passive acceptance but active advocacy. This finding is all the more significant when considered alongside the rest of the survey, which makes clear that respondents are fully aware of the risks, resource demands, and governance challenges that data collaboration entails. Their endorsement is therefore neither naive nor uninformed. It is the considered judgement of experienced practitioners who believe, despite the challenges, that the potential of data collaboration far outweighs its costs.

The Value Proposition Is Well Understood

Respondents demonstrated a clear and consistent understanding of what data collaboration can offer. Across the range of expected benefits presented in the survey, the strongest resonance was with those that speak most directly to the day-to-day realities of cultural management: access to richer, more diverse datasets for deeper audience insight; improved decision-making grounded in higher-quality and more timely evidence; and better benchmarking tools that allow organisations to contextualise their own performance within a broader sector picture. These are not abstract aspirations — they reflect a genuine appetite for the kind of systemic, evidence-led understanding of audiences that individual organisations, working in isolation, simply cannot achieve on their own.

Cost savings through shared infrastructure and the potential for accelerated innovation also attracted meaningful support, though these benefits were perhaps seen as secondary to the core value proposition of richer, more actionable insight. Taken together, the responses to this section paint a picture of a sector that understands not just the principle of data collaboration, but its practical relevance to the work it does every day.

Concerns Are Real, But Not Prohibitive

While enthusiasm for data collaboration is high, respondents were equally candid about the concerns and risks they associate with it. Privacy and data security emerged as a significant area of concern, reflecting the heightened awareness of data protection obligations that has characterised the sector — and indeed all public-facing organisations — since the introduction of GDPR across Europe. Legal and regulatory constraints, questions about data quality and provenance, and the potential for competitive disadvantage were also identified as meaningful risks that any data collaboration framework would need to address.

Critically, however, the qualitative responses to this section were notable not for their resistance to collaboration, but for their constructive orientation toward solutions. One respondent observed that “a good overall governance model to make sure that standards are used properly" would be central to managing these concerns, while another noted that “many of these concerns can be overcome with the right approach to anonymised" data — a comment that, even in its truncated form, speaks clearly to the role of technical and procedural safeguards in building trust. The message from respondents is not that risks make collaboration impossible, but that they make governance design absolutely essential.

Resources and Capacity Remain a Barrier

The survey also highlighted the resource landscape within which cultural organisations would need to operate if they were to participate meaningfully in data collaboration. Respondents identified access to skilled data personnel, standard collaboration platforms and dashboards, and data literacy training as important prerequisites for participation — findings that are consistent with what is broadly known about capacity constraints in the cultural sector. Organisations that are already stretched in terms of staffing and budgets cannot simply absorb the demands of data collaboration without appropriate support.

One respondent's observation about the need for systems interoperability points to a more technical dimension of this resource challenge. The ability to connect datasets across organisations is not simply a matter of will or governance — it requires compatible infrastructure, shared data standards, and the technical expertise to implement them. This is a particularly important consideration for any initiative that aims to operate at a European, transnational scale, where the diversity of existing systems and national data environments adds further complexity.

Structural Challenges Are Widely Acknowledged

Beyond organisational resources, respondents were asked to reflect on the broader structural challenges facing data collaboration in the cultural sector. The responses converged strongly around a familiar set of barriers: data silos and inconsistent data quality, skills gaps and insufficient budgets, inadequate governance and compliance frameworks, and limited access to the external datasets that would give collaborative insights their full analytical power. These are not new problems, and their presence in this survey confirms that the ambition to collaborate must be accompanied by a realistic plan to address the infrastructure and capability gaps that currently stand in the way.

Governance and Ownership Are Non-Negotiable

When asked about preferred models for delivering data collaboration, respondents showed the strongest affinity for approaches that place cultural organisations themselves at the centre — whether through sector-led governance, national or transnational policy frameworks, or thoughtfully designed hybrid models. There was considerably less enthusiasm for arrangements led or managed primarily by commercial entities, reflecting a deeply held instinct within the cultural sector that its data, and the insights derived from it, should remain under the stewardship of those who generated it.

The qualitative responses to this section were particularly illuminating. One respondent captured the mood succinctly by noting that, in their view, the answer was “all of the above", but with an important caveat: “cultural organizations should not get a feeling that..." — a sentence that, though truncated, almost certainly points to concerns about loss of agency, top-down imposition, or being subject to arrangements they have had no hand in designing. This finding carries significant implications for how the Data Collaboration Canvas is positioned and communicated. Co-design, transparency, and genuine sector ownership are not optional features of a successful data collaboration framework — they are foundational conditions for its legitimacy and uptake.